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BMCBI
2002
195views more  BMCBI 2002»
14 years 9 months ago
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
Background: A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expressio...
Junbai Wang, Jan Delabie, Hans Christian Aasheim, ...
BMCBI
2004
169views more  BMCBI 2004»
14 years 9 months ago
A power law global error model for the identification of differentially expressed genes in microarray data
Background: High-density oligonucleotide microarray technology enables the discovery of genes that are transcriptionally modulated in different biological samples due to physiolog...
Norman Pavelka, Mattia Pelizzola, Caterina Vizzard...
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CSB
2005
IEEE
137views Bioinformatics» more  CSB 2005»
15 years 3 months ago
A Learned Comparative Expression Measure for Affymetrix GeneChip DNA Microarrays
Perhaps the most common question that a microarray study can ask is, “Between two given biological conditions, which genes exhibit changed expression levels?” Existing methods...
Will Sheffler, Eli Upfal, John Sedivy, William Sta...
BMCBI
2007
157views more  BMCBI 2007»
14 years 9 months ago
Improving gene set analysis of microarray data by SAM-GS
Background: Gene-set analysis evaluates the expression of biological pathways, or a priori defined gene sets, rather than that of individual genes, in association with a binary ph...
Irina Dinu, John D. Potter, Thomas Mueller, Qi Liu...
BMCBI
2005
113views more  BMCBI 2005»
14 years 9 months ago
Normal uniform mixture differential gene expression detection for cDNA microarrays
Background: One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the ...
Nema Dean, Adrian E. Raftery